fix: full CSV download in AgGrid

superset-frontend/src/dashboard/components/SliceHeaderControls/SliceHeaderControls.test.tsx

@@ -237,6 +237,20 @@ test('Should "export full CSV"', async () => {
   expect(props.exportFullCSV).toHaveBeenCalledWith(371);
 });
 
+test('Should "export full CSV" for ag-grid table', async () => {
+  (global as any).featureFlags = {
+    [FeatureFlag.AllowFullCsvExport]: true,
+  };
+  const props = createProps(VizType.TableAgGrid);
+  renderWrapper(props);
+  openMenu();
+  expect(props.exportFullCSV).toHaveBeenCalledTimes(0);
+  userEvent.hover(screen.getByText('Download'));
+  userEvent.click(await screen.findByText('Export to full .CSV'));
+  expect(props.exportFullCSV).toHaveBeenCalledTimes(1);
+  expect(props.exportFullCSV).toHaveBeenCalledWith(371);
+});
+
 test('Should not show export full CSV if report is not table', async () => {
   (global as any).featureFlags = {
     [FeatureFlag.AllowFullCsvExport]: true,
@@ -274,6 +288,20 @@ test('Should "export full Excel"', async () => {
   expect(props.exportFullXLSX).toHaveBeenCalledWith(371);
 });
 
+test('Should "export full Excel" for ag-grid table', async () => {
+  (global as any).featureFlags = {
+    [FeatureFlag.AllowFullCsvExport]: true,
+  };
+  const props = createProps(VizType.TableAgGrid);
+  renderWrapper(props);
+  openMenu();
+  expect(props.exportFullXLSX).toHaveBeenCalledTimes(0);
+  userEvent.hover(screen.getByText('Download'));
+  userEvent.click(await screen.findByText('Export to full Excel'));
+  expect(props.exportFullXLSX).toHaveBeenCalledTimes(1);
+  expect(props.exportFullXLSX).toHaveBeenCalledWith(371);
+});
+
 test('Should not show export full Excel if report is not table', async () => {
   (global as any).featureFlags = {
     [FeatureFlag.AllowFullCsvExport]: true,

superset-frontend/src/dashboard/components/SliceHeaderControls/index.tsx

@@ -372,7 +372,8 @@ const SliceHeaderControls = (
     supersetCanShare = false,
     isCached = [],
   } = props;
-  const isTable = slice.viz_type === VizType.Table;
+  const isTable =
+    slice.viz_type === VizType.Table || slice.viz_type === VizType.TableAgGrid;
   const isPivotTable = slice.viz_type === VizType.PivotTable;
   const cachedWhen = (cachedDttm || []).map(itemCachedDttm =>
     (extendedDayjs.utc(itemCachedDttm) as any).fromNow(),

superset/semantic_layers/models.py

@@ -43,10 +43,6 @@ from superset_core.semantic_layers.view import (
 )
 
 from superset.common.query_object import QueryObject
-from superset.exceptions import (
-    InvalidPostProcessingError,
-    QueryObjectValidationError,
-)
 from superset.explorables.base import TimeGrainDict
 from superset.extensions import encrypted_field_factory
 from superset.models.helpers import AuditMixinNullable, QueryResult
@@ -285,13 +281,7 @@ class SemanticView(AuditMixinNullable, Model):
     # =========================================================================
 
     def get_query_result(self, query_object: QueryObject) -> QueryResult:
-        result = get_results(query_object)
-        if query_object.post_processing and not result.df.empty:
-            try:
-                result.df = query_object.exec_post_processing(result.df)
-            except InvalidPostProcessingError as ex:
-                raise QueryObjectValidationError(ex.message) from ex
-        return result
+        return get_results(query_object)
 
     def get_query_str(self, query_obj: QueryObjectDict) -> str:
         return "Not implemented for semantic layers"

tests/unit_tests/semantic_layers/models_test.py

@@ -662,7 +662,6 @@ def test_semantic_view_get_query_result(
     view = SemanticView()
 
     mock_query_object = MagicMock()
-    mock_query_object.post_processing = []
     mock_result = MagicMock()
 
     with patch(
@@ -672,115 +671,9 @@ def test_semantic_view_get_query_result(
         result = view.get_query_result(mock_query_object)
 
         mock_get_results.assert_called_once_with(mock_query_object)
-        mock_query_object.exec_post_processing.assert_not_called()
         assert result == mock_result
 
 
-def test_semantic_view_get_query_result_runs_post_processing(
-    mock_implementation: MagicMock,
-) -> None:
-    """
-    ``get_query_result`` must run ``query_object.exec_post_processing`` so that
-    features like ``percent_metrics`` (contribution) are applied to the semantic
-    layer's DataFrame — matching the dataset flow in
-    ``superset/models/helpers.py``.
-    """
-    import pandas as pd
-
-    view = SemanticView()
-
-    input_df = pd.DataFrame({"Orders Count": [40000.0]})
-    processed_df = pd.DataFrame({"Orders Count": [40000.0], "%Orders Count": [1.0]})
-
-    mock_query_object = MagicMock()
-    mock_query_object.post_processing = [
-        {
-            "operation": "contribution",
-            "options": {
-                "columns": ["Orders Count"],
-                "rename_columns": ["%Orders Count"],
-            },
-        }
-    ]
-    mock_query_object.exec_post_processing.return_value = processed_df
-
-    mock_result = MagicMock()
-    mock_result.df = input_df
-
-    with patch(
-        "superset.semantic_layers.models.get_results",
-        return_value=mock_result,
-    ):
-        result = view.get_query_result(mock_query_object)
-
-    mock_query_object.exec_post_processing.assert_called_once_with(input_df)
-    assert result is mock_result
-    assert list(result.df.columns) == ["Orders Count", "%Orders Count"]
-
-
-def test_semantic_view_get_query_result_wraps_post_processing_errors(
-    mock_implementation: MagicMock,
-) -> None:
-    """
-    ``InvalidPostProcessingError`` raised from post-processing must be re-raised
-    as ``QueryObjectValidationError`` so the API surfaces a clean 400 rather
-    than a 500.
-    """
-    import pandas as pd
-
-    from superset.exceptions import (
-        InvalidPostProcessingError,
-        QueryObjectValidationError,
-    )
-
-    view = SemanticView()
-
-    mock_query_object = MagicMock()
-    mock_query_object.post_processing = [{"operation": "bogus"}]
-    mock_query_object.exec_post_processing.side_effect = InvalidPostProcessingError(
-        "boom"
-    )
-
-    mock_result = MagicMock()
-    mock_result.df = pd.DataFrame({"count": [1]})
-
-    with (
-        patch(
-            "superset.semantic_layers.models.get_results",
-            return_value=mock_result,
-        ),
-        pytest.raises(QueryObjectValidationError, match="boom"),
-    ):
-        view.get_query_result(mock_query_object)
-
-
-def test_semantic_view_get_query_result_skips_post_processing_on_empty_df(
-    mock_implementation: MagicMock,
-) -> None:
-    """
-    Match the dataset flow's guard: skip post-processing when the DataFrame is
-    empty. Contribution and other ops assume at least one row.
-    """
-    import pandas as pd
-
-    view = SemanticView()
-
-    mock_query_object = MagicMock()
-    mock_query_object.post_processing = [{"operation": "contribution"}]
-
-    mock_result = MagicMock()
-    mock_result.df = pd.DataFrame()
-
-    with patch(
-        "superset.semantic_layers.models.get_results",
-        return_value=mock_result,
-    ):
-        result = view.get_query_result(mock_query_object)
-
-    mock_query_object.exec_post_processing.assert_not_called()
-    assert result is mock_result
-
-
 def test_semantic_view_data_for_slices(
     mock_implementation: MagicMock,
     mock_dimensions: list[Dimension],